Analysis of Tiling Array Expression Studies with Flexible Designs in Bioconductor (waveTiling)

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2012 Sep 15

PMID 22974078

Authors

Kristof De Beuf

Peter Pipelers

Megan Andriankaja

Olivier Thas

Dirk Inze

Ciprian Crainiceanu

Lieven Clement

Affiliations

Soon will be listed here.

Abstract

Background: Existing statistical methods for tiling array transcriptome data either focus on transcript discovery in one biological or experimental condition or on the detection of differential expression between two conditions. Increasingly often, however, biologists are interested in time-course studies, studies with more than two conditions or even multiple-factor studies. As these studies are currently analyzed with the traditional microarray analysis techniques, they do not exploit the genome-wide nature of tiling array data to its full potential.

Results: We present an R Bioconductor package, waveTiling, which implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling the user is able to discover (1) group-wise expressed regions, (2) differentially expressed regions between any two groups in single-factor studies and in (3) multifactorial designs. Moreover, for time-course experiments it is also possible to detect (4) linear time effects and (5) a circadian rhythm of transcripts. By considering the expression values of the individual tiling probes as a function of genomic position, effect regions can be detected regardless of existing annotation. Three case studies with different experimental set-ups illustrate the use and the flexibility of the model-based transcriptome analysis.

Conclusions: The waveTiling package provides the user with a convenient tool for the analysis of tiling array trancriptome data for a multitude of experimental set-ups. Regardless of the study design, the probe-wise analysis allows for the detection of transcriptional effects in both exonic, intronic and intergenic regions, without prior consultation of existing annotation.

References

de Lichtenberg U, Jensen L, Fausboll A, Jensen T, Bork P, Brunak S . Comparison of computational methods for the identification of cell cycle-regulated genes. Bioinformatics. 2004; 21(7):1164-71. DOI: 10.1093/bioinformatics/bti093. View

Assarsson E, Greenbaum J, Sundstrom M, Schaffer L, Hammond J, Pasquetto V . Kinetic analysis of a complete poxvirus transcriptome reveals an immediate-early class of genes. Proc Natl Acad Sci U S A. 2008; 105(6):2140-5. PMC: 2542872. DOI: 10.1073/pnas.0711573105. View

Samanta M, Tongprasit W, Sethi H, Chin C, Stolc V . Global identification of noncoding RNAs in Saccharomyces cerevisiae by modulating an essential RNA processing pathway. Proc Natl Acad Sci U S A. 2006; 103(11):4192-7. PMC: 1389707. DOI: 10.1073/pnas.0507669103. View

Gardner M, Hubbard K, Hotta C, Dodd A, Webb A . How plants tell the time. Biochem J. 2006; 397(1):15-24. PMC: 1479754. DOI: 10.1042/BJ20060484. View

Swarbreck D, Wilks C, Lamesch P, Berardini T, Garcia-Hernandez M, Foerster H . The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res. 2007; 36(Database issue):D1009-14. PMC: 2238962. DOI: 10.1093/nar/gkm965. View

Carvalho B, Irizarry R . A framework for oligonucleotide microarray preprocessing. Bioinformatics. 2010; 26(19):2363-7. PMC: 2944196. DOI: 10.1093/bioinformatics/btq431. View

Hazen S, Naef F, Quisel T, Gendron J, Chen H, Ecker J . Exploring the transcriptional landscape of plant circadian rhythms using genome tiling arrays. Genome Biol. 2009; 10(2):R17. PMC: 2688271. DOI: 10.1186/gb-2009-10-2-r17. View

Durinck S, Bullard J, Spellman P, Dudoit S . GenomeGraphs: integrated genomic data visualization with R. BMC Bioinformatics. 2009; 10:2. PMC: 2629762. DOI: 10.1186/1471-2105-10-2. View

Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S . Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004; 5(10):R80. PMC: 545600. DOI: 10.1186/gb-2004-5-10-r80. View

10.

Morris J, Brown P, Herrick R, Baggerly K, Coombes K . Bayesian analysis of mass spectrometry proteomic data using wavelet-based functional mixed models. Biometrics. 2007; 64(2):479-89. PMC: 2659628. DOI: 10.1111/j.1541-0420.2007.00895.x. View

11.

Andriankaja M, Dhondt S, de Bodt S, Vanhaeren H, Coppens F, De Milde L . Exit from proliferation during leaf development in Arabidopsis thaliana: a not-so-gradual process. Dev Cell. 2012; 22(1):64-78. DOI: 10.1016/j.devcel.2011.11.011. View

12.

Stolc V, Samanta M, Tongprasit W, Sethi H, Liang S, Nelson D . Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays. Proc Natl Acad Sci U S A. 2005; 102(12):4453-8. PMC: 555476. DOI: 10.1073/pnas.0408203102. View

13.

Tusher V, Tibshirani R, Chu G . Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A. 2001; 98(9):5116-21. PMC: 33173. DOI: 10.1073/pnas.091062498. View

14.

Smyth G . Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2006; 3:Article3. DOI: 10.2202/1544-6115.1027. View

15.

Toyoda T, Shinozaki K . Tiling array-driven elucidation of transcriptional structures based on maximum-likelihood and Markov models. Plant J. 2005; 43(4):611-21. DOI: 10.1111/j.1365-313X.2005.02470.x. View

16.

Wijnen H, Naef F, Young M . Molecular and statistical tools for circadian transcript profiling. Methods Enzymol. 2005; 393:341-65. DOI: 10.1016/S0076-6879(05)93015-2. View

17.

Granovskaia M, Jensen L, Ritchie M, Toedling J, Ning Y, Bork P . High-resolution transcription atlas of the mitotic cell cycle in budding yeast. Genome Biol. 2010; 11(3):R24. PMC: 2864564. DOI: 10.1186/gb-2010-11-3-r24. View

18.

Matsui A, Ishida J, Morosawa T, Mochizuki Y, Kaminuma E, Endo T . Arabidopsis transcriptome analysis under drought, cold, high-salinity and ABA treatment conditions using a tiling array. Plant Cell Physiol. 2008; 49(8):1135-49. DOI: 10.1093/pcp/pcn101. View

19.

Schadt E, Edwards S, GuhaThakurta D, Holder D, Ying L, Svetnik V . A comprehensive transcript index of the human genome generated using microarrays and computational approaches. Genome Biol. 2004; 5(10):R73. PMC: 545593. DOI: 10.1186/gb-2004-5-10-r73. View

20.

Qu Y, Xu S . Quantitative trait associated microarray gene expression data analysis. Mol Biol Evol. 2006; 23(8):1558-73. DOI: 10.1093/molbev/msl019. View